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Record W2999316058 · doi:10.1108/jmd-06-2019-0253

Organizational culture, innovation and performance: a study from a non-western context

2019· article· en· W2999316058 on OpenAlexaff
Mohammed Aboramadan, Belal Albashiti, Hatem Alharazin, Souhaila Zaidoune

Bibliographic record

VenueJournal of Management Development · 2019
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsOrganizational cultureOrganizational performanceOriginalityContext (archaeology)BusinessMarketingValue (mathematics)Knowledge managementPublic relationsSociologyPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine the links between organizational culture, innovation and banks’ performance in Palestine. Design/methodology/approach Data were gathered from 186 employees working in the Palestinian banking sector. The data gathered were analyzed using the PLS-SEM approach. Findings The findings of the study show that organizational culture and marketing innovation have a positive impact on banks’ performance. Moreover, it was found that marketing performance partially mediates the relationship between organizational culture and banks’ performance. Practical implications The paper may be of use for banks managers to create an organizational culture, which fosters both innovation and performance. Originality/value The paper is unique as it examines organizational culture, innovation and performance links in a non-western context.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.212
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations178
Published2019
Admission routes1
Has abstractyes

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